Genes, maternal smoking and the offspring brain and body during adolescence: Design of The Saguenay Youth Study

Brain and Body Centre, University of Nottingham, Nottingham, United Kingdom.
Human Brain Mapping (Impact Factor: 5.97). 07/2007; 28(6):502-18. DOI: 10.1002/hbm.20402
Source: PubMed


The search for genes of complex traits is aided by the availability of multiple quantitative phenotypes collected in geographically isolated populations. Here we provide rationale for a large-scale study of gene-environment interactions influencing brain and behavior and cardiovascular and metabolic health in adolescence, namely the Saguenay Youth Study (SYS). The SYS is a retrospective study of long-term consequences of prenatal exposure to maternal cigarette smoking (PEMCS) in which multiple quantitative phenotypes are acquired over five sessions (telephone interview, home, hospital, laboratory, and school). To facilitate the search for genes that modify an individual's response to an in utero environment (i.e. PEMCS), the study is family-based (adolescent sibships) and is carried out in a relatively geographically isolated population of the Saguenay Lac-Saint-Jean (SLSJ) region in Quebec, Canada. DNA is acquired in both biological parents and in adolescent siblings. A genome-wide scan will be carried out with sib-pair linkage analyses, and fine mapping of identified loci will be done with family-based association analyses. Adolescent sibships (12-18 years of age; two or more siblings per family) are recruited in high schools throughout the SLSJ region; only children of French-Canadian origin are included. Based on a telephone interview, potential participants are classified as exposed or nonexposed prenatally to maternal cigarette smoking; the two groups are matched for the level of maternal education and the attended school. A total of 500 adolescent participants in each group will be recruited and phenotyped. The following types of datasets are collected in all adolescent participants: (1) magnetic resonance images of brain, abdominal fat, and kidneys, (2) standardized and computer-based neuropsychological tests, (3) hospital-based cardiovascular, body-composition and metabolic assessments, and (4) questionnaire-derived measures (e.g. life habits such as eating and physical activity; drug, alcohol use and delinquency; psychiatric symptoms; personality; home and school environment; academic and vocational attitudes). Parents complete a medical questionnaire, home-environment questionnaire, a handedness questionnaire, and a questionnaire about their current alcohol and drug use, depression, anxiety, and current and past antisocial behavior. To date, we have fully phenotyped a total of 408 adolescent participants. Here we provide the description of the SYS and, using the initial sample, we present information on ascertainment, demographics of the exposed and nonexposed adolescents and their parents, and the initial MRI-based assessment of familiality in the brain size and the volumes of grey and white matter.

1 Follower
9 Reads
  • Source
    • "We acquired MRI, puberty information, and hormone concentrations in the Saguenay Youth Study, a large community-based sample of adolescents from the Saguenay-Lac-Saint-Jean region of Québec. Details for the participant recruitment and testing procedures are described elsewhere (Pausova et al. 2007; Perrin et al. 2008). Table 1 includes the sample details for participants included in the T1W analyses by sex (number of participants, mean age and mean puberty score). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Some of the known sex differences in white matter emerge during adolescence. Here, we replicate and extend our previous findings of sex differences in the structure of the corticospinal tract (Perrin et al. 2009; Hervé et al. 2009). In a large normative sample of adolescents, we observed age × sex interactions in the signal intensity of T1-weighted (T1W) images (n = 941) and in magnetization transfer ratio (MTR; n = 761); both features were inversely associated with age in males but not in females. Moreover, we hypothesized that the age-related differences in CST structure exhibited by males would be mediated by differences in puberty stage and levels of bioavailable testosterone. We confirmed this prediction using mediation analysis with bootstrapping. These findings suggest that sex differences in the CST structure observed during male adolescence may be due to multiple processes associated with puberty, including (but not limited to) the rising levels of testosterone.
    Brain Structure and Function 12/2014; DOI:10.1007/s00429-014-0956-9 · 5.62 Impact Factor
  • Source
    • "We used a family-based design, recruiting a minimum of two siblings per family; note that siblings were concordant for the exposure status in the majority of families (446/481 families; 93%). Phenotyping of the adolescents took place over several sessions (∼15 h in total) and included a number of domains detailed in Table 1 (further details in Pausova et al., 2007 and; each adolescent provided a fasting (morning) blood sam- ple. "
    [Show abstract] [Hide abstract]
    ABSTRACT: This paper provides an overview of the Saguenay Youth Study (SYS) and its parental arm. The overarching goal of this effort is to develop trans-generational models of developmental cascades contributing to the emergence of common chronic disorders, such as depression, addictions, dementia and cardio-metabolic diseases. Over the past 10 years, we have acquired detailed brain and cardio-metabolic phenotypes, and genome-wide genotypes, in 1029 adolescents recruited in a population with a known genetic founder effect. At present, we are extending this dataset to acquire comparable phenotypes and genotypes in the biological parents of these individuals. After providing conceptual background for this work (transactions across time, systems and organs), we describe briefly the tools employed in the adolescent arm of this cohort and highlight some of the initial accomplishments. We then outline in detail the phenotyping protocol used to acquire comparable data in the parents.
    Developmental Cognitive Neuroscience 10/2014; 11. DOI:10.1016/j.dcn.2014.10.003 · 3.83 Impact Factor
  • Source
    • "Based on post-mortem data, Frahm and colleagues estimated the volume of ''cortical'' 1 WM to be $420 cm 3 , or 42% of the total volume (Frahm et al., 1982). Using magnetic resonance (MR) images collected in 1000 typically developing adolescents participating in the Saguenay Youth Study (Pausova et al., 2007), we obtained similar figures for male (456 ± 48 cm 3 , 39.9 ± 2.7%; n = 476) and female (392 ± 42 cm 3 , 38.6 ± 2.5%; n = 509) adolescents. "
    [Show abstract] [Hide abstract]
    ABSTRACT: There are two ways to picture white matter: as a grid of electrical wires or a network of roads. The first metaphor captures the classical function of an axon as conductor of action potentials (and information) from one brain region to another. The second one points to the important role of axons in a bi-directional transport of biological molecules and organelles between the cell body and synapse. Given the wide variety of such cargoes, a well-functioning axonal transport is critical for a number of processes, including neurotransmission, metabolism and viability of neurons. This selective review will emphasize the need for considering axonal transport when interpreting functional consequences of inter-individual variations in the structural properties of white matter. We start by describing the space occupied by white matter and techniques used in vivo for its characterization. We then provide examples of key features of maturation and aging of white matter, as well as some of the common abnormalities observed in neurodevelopmental and neurodegenerative disorders. Next, we review work that motivated our focus on axonal diameter, and explain the relationships between transport and cytoskeleton within the axon. We will conclude by describing molecular machinery of axonal transport and genes that may contribute to inter-individual variations in axonal diameter and axonal transport.
    Neuroscience 02/2014; 276. DOI:10.1016/j.neuroscience.2014.01.055 · 3.36 Impact Factor
Show more